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ease
features
design
support

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Description

Cribl Search introduces an innovative search-in-place technology that allows users to effortlessly explore, discover, and analyze data that was once deemed inaccessible, directly from its source and across various cloud environments, including data secured behind APIs. Users can easily navigate through their Cribl Lake or examine data stored in prominent object storage solutions such as AWS S3, Amazon Security Lake, Azure Blob, and Google Cloud Storage, while also enriching their insights by querying multiple live API endpoints from a variety of SaaS providers. The core advantage of Cribl Search is its strategic capability to forward only the essential data to analytical systems, thus minimizing the expenses associated with storage. With built-in compatibility for platforms like Amazon Security Lake, AWS S3, Azure Blob, and Google Cloud Storage, Cribl Search offers a unique opportunity to analyze all data directly where it resides. Furthermore, it empowers users to conduct searches and analyses on data regardless of its location, whether it be debug logs at the edge or data archived in cold storage, thereby enhancing their data-driven decision-making. This versatility in data access significantly streamlines the process of gaining insights from diverse data sources.

Description

Open core technology facilitates the integration of hybrid and multi-cloud environments. Built on the open-source initiative CDAP, Data Fusion guarantees portability of data pipelines for its users. The extensive compatibility of CDAP with both on-premises and public cloud services enables Cloud Data Fusion users to eliminate data silos and access previously unreachable insights. Additionally, its seamless integration with Google’s top-tier big data tools enhances the user experience. By leveraging Google Cloud, Data Fusion not only streamlines data security but also ensures that data is readily available for thorough analysis. Whether you are constructing a data lake utilizing Cloud Storage and Dataproc, transferring data into BigQuery for robust data warehousing, or transforming data for placement into a relational database like Cloud Spanner, the integration capabilities of Cloud Data Fusion promote swift and efficient development while allowing for rapid iteration. This comprehensive approach ultimately empowers businesses to derive greater value from their data assets.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

AWS Security Hub
Amazon S3
Azure Blob Storage
Cribl AppScope
Cribl Edge
Cribl Lake
Cribl Stream
Dropbox Dash
Google Cloud BigQuery
Google Cloud Datastream
Google Cloud Platform
Google Cloud Storage
Google Workspace
IntelliPay
Microsoft Azure
Okta
Pantomath
Zoom

Integrations

AWS Security Hub
Amazon S3
Azure Blob Storage
Cribl AppScope
Cribl Edge
Cribl Lake
Cribl Stream
Dropbox Dash
Google Cloud BigQuery
Google Cloud Datastream
Google Cloud Platform
Google Cloud Storage
Google Workspace
IntelliPay
Microsoft Azure
Okta
Pantomath
Zoom

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Cribl

Founded

2018

Country

United States

Website

cribl.io/search/

Vendor Details

Company Name

Google

Country

United States

Website

cloud.google.com/data-fusion

Product Features

Enterprise Search

AI / Machine Learning
Faceted Search / Filtering
Full Text Search
Fuzzy Search
Indexing
Text Analytics
eDiscovery

Product Features

ETL

Data Analysis
Data Filtering
Data Quality Control
Job Scheduling
Match & Merge
Metadata Management
Non-Relational Transformations
Version Control

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